Unify your data so every other system can be trusted

AxionIQ unifies the data behind your CRM, accounting, helpdesk and payments into one live, reconciled view. Every AI agent, dashboard and decision that follows is built on numbers that actually tie out. The best AI is worthless on bad data, so we start here.

What it does

We connect your operational sources (Salesforce, HubSpot, Shopify, Stripe, Xero, QuickBooks, NetSuite, Zendesk, Intercom, your data warehouse) into a single modelled layer. Customer, order, invoice and ticket become entities the whole business agrees on. Revenue ties out across systems. Duplicates collapse. Reporting stops disagreeing with itself.

On top of that layer we build the dashboards the team actually uses: revenue and cash by week, pipeline health, support response times and CSAT, marketing attribution that respects your real customer journey, and operations KPIs by team. Dashboards run on live data, not a Monday-morning spreadsheet pull.

How AxionIQ implements it

We start with a one-week data audit: which sources hold the truth for each entity, where duplicates live, where reconciliation breaks. We pick the warehouse (typically BigQuery or Postgres), set up ingestion through Fivetran, Airbyte or direct API where it matters, and model the core entities in dbt. We then build the first dashboard against the metric you care about most. The first thing you see is the reconciliation, not the dashboard, so you trust the numbers before you use them.

Under Build & Run we operate the pipelines, monitor freshness and reconciliation, and roll in new sources or metrics as your business changes. You do not need to hire a data engineer.

ROI examples

A multi-brand e-commerce operator collapsed five conflicting weekly revenue reports into one reconciled view that the founder, finance and marketing all trust. A B2B SaaS company tied marketing spend to pipeline by source for the first time, and reallocated budget away from a channel that had been overstated by 40 percent in their old dashboard. A logistics business cut three hours a week of manual ledger reconciliation by tying Stripe, the OMS and Xero through a single modelled customer.

Where this fits

Data unification is the foundation for AI agents for operations and meaningful customer support automation. Without it, agents act on wrong data and lose trust within a week. Strongest fit: e-commerce, logistics and estate agents.

Common questions

Do we need a data warehouse to start?

For most SMEs, yes. We typically stand up BigQuery, Snowflake or Postgres depending on volume, cost and your existing cloud. For under one million rows across a handful of sources, a managed Postgres is plenty. We size the architecture to the business, not the buzzword.

How long until we trust the numbers?

Two to four weeks for a first reliable dashboard on three to five sources. We start with reconciliation: revenue in Stripe must match revenue in your CRM must match revenue in Xero. Until those tie out, we do not ship dashboards. Trust comes from the tie-out, not the chart.

Will this replace our existing reporting?

Often, yes. Spreadsheets pulled together by hand each Monday morning typically disappear within a quarter, because the live dashboard is more accurate and saves the analyst three to five hours a week. We migrate, we do not duplicate.